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Despite their enormous potential, the use of indoor localization systems (ILS) remains seldom. One reason is the lack of market transparency and stakeholders’ trust in the systems’ performance as a consequence of insufficient use of test and evaluation (T&E) methodologies. The heterogeneous nature of ILS, their influences, and their applications po...
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... goal of the Application Definition is to describe exactly what the application or application domain under consideration (AUC) looks like, whereby an application domain contains multiple applications. The functions of the Application Definition are shown in Figure 4. First, the aim of the AUC is described (1). ...
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... To be meaningful from the end user's perspective, the testing procedure and performance metrics should meet the application requirements. Currently, an application-driven framework is being developed that aims at the meaningful testing and evaluation of ILS [14]. Future work will integrate the discussed concepts and the presented method presented into a holistic approach for application-driven testing and evaluation of ILS. ...
Various applications leverage location data to increase transparency, efficiency, and safety in intralogistics. There are several properties of location data, such as the data's degrees of freedom, system latency, update rate, or accuracy. To select a suitable indoor localization system, corresponding data requirements must be derived by analyzing the considered application. To date, the dependencies of the system performance and location data requirements have not been satisfactorily described in the literature. Thus, no method exists to adequately derive location data requirements. For intralogistics, such a method is of particular relevance due to the high-cost sensitivity and heterogeneity of partially safety-relevant indoor localization applications. To fill this gap, a method for selecting and quantifying location data requirements for the application in intralogistics is presented in this work, creating substantial added value for warehouse managers and system integrators. The method is based on a spatial model that is built on the premise that location data is used to determine the presence or absence of an entity in a multidimensional interest space. The usage of the method is demonstrated in an exemplary case study for the application of 'Automated Pallet Booking'.
... To be meaningful from the end user's perspective, the testing procedure and performance metrics should meet the application requirements. Currently, an application-driven framework is being developed that aims at the meaningful testing and evaluation of ILS [14]. Future work will integrate the discussed concepts and the presented method presented into a holistic approach for application-driven testing and evaluation of ILS. ...
Various applications leverage location data to increase transparency, efficiency, and safety in intralogistics. There are several properties of location data, such as the data's degrees of freedom, system latency, update rate, or accuracy. To select a suitable indoor localization system, corresponding data requirements must be derived by analyzing the considered application. To date, the dependencies of the system performance and location data requirements have not been satisfactorily described in the literature. Thus, no method exists to adequately derive location data requirements. For intralogistics, such a method is of particular relevance due to the high-cost sensitivity and heterogeneity of partially safety-relevant indoor localization applications. To fill this gap, a method for selecting and quantifying location data requirements for the application in intralogistics is presented in this work, creating substantial added value for warehouse managers and system integrators. The method is based on a spatial model that is built on the premise that location data is used to determine the presence or absence of an entity in a multidimensional interest space. The usage of the method is demonstrated in an exemplary case study for the application of 'Automated Pallet Booking'.
... Schyga et al. [15] also deal with the evaluation problem and the difficulty to compare results among different sources. They propose the T&E 4iLoc Framework, a methodology for T&E of indoor localization systems in semi-controlled environments based on a system-level and black-box approach, which is highly reproducible and, therefore, facilitates comparison. ...
Locating devices in indoor environments has become a key issue for many emerging location-based applications and intelligent spaces in different fields [...]
... Approaches for T&E can be divided into system vs. component-testing, black-box vs. white-box (or grey-box) testing, or building-wide vs. laboratory testing [15,16]. Influences can be considered for the experiment design and/or for analysis. ...
... As for the consideration of influences, the EvAAL Framework only requires the building, the path, and the entity to be localized to represent the considered application [22], while the ISO/IEC 18305 [15] additionally suggests to include particularly challenging experiments for the system under test. The T&E 4iLoc Framework [16] proposes a procedure to systematically define applicationdriven influencing factors and transpose them into an experiment in a semi-controlled test environment such as a test hall. Finally, the EVARILOS Benchmarking Handbook [23] proposes the systematic analysis of influences from changes in the environment, mobility, amount of radio-frequency nodes, or radio interference to a reference scenario individually. ...
... In step A of Figure 2, performance metrics are collected from experiments under several different scenarios. To ensure repeatability of results for the complex experiment scenario, the T&E 4iLoc Framework [16] is utilized as methodology. ...
... Approaches for T&E can be divided into system vs. component-testing, black-box vs. white-box (or grey-box) testing, or building-wide vs. laboratory testing [15,16]. Influences can be considered for the experiment design and/or for analysis. ...
... As for the consideration of influences, the EvAAL Framework only requires the building, the path, and the entity to be localized to represent the considered application [22], while the ISO/IEC 18305 [15] additionally suggests to include particularly challenging experiments for the system under test. The T&E 4iLoc Framework [16] proposes a procedure to systematically define applicationdriven influencing factors and transpose them into an experiment in a semi-controlled test environment such as a test hall. Finally, the EVARILOS Benchmarking Handbook [23] proposes the systematic analysis of influences from changes in the environment, mobility, amount of radio-frequency nodes, or radio interference to a reference scenario individually. ...
... In step A of Figure 2, performance metrics are collected from experiments under several different scenarios. To ensure repeatability of results for the complex experiment scenario, the T&E 4iLoc Framework [16] is utilized as methodology. ...
Absolute position accuracy is the key performance criterion of an Indoor Localization System (ILS). Since ILS are heterogeneous and complex cyber-physical systems, the localization accuracy depends on various influences from the environment, system configuration, and the application processes. To determine the position accuracy of a system in a reproducible, comparable, and realistic manner, these factors must be taken into account. We propose a strategy for analyzing the influences on the position accuracy of ILS using decision trees in combination with application-related or technology-related categorization. The proposed strategy is validated using empirical data from 120 experiments. The accuracy of an Ultra-Wideband and a LiDAR-based ILS was determined under different application-driven influencing factors, considering the application of autonomous mobile robots in warehouses. Finally, the opportunities and limitations of analyzing decision trees to compare system performance, find a suitable system, optimize the environment or system configuration, and understand the relevance of different influencing factors are presented.
... Approaches for T&E can be divided into system vs. component-testing, black-box vs. white-box (or grey-box) testing, or building-wide vs. laboratory testing [15,16]. Influences can be considered for the experiment design and/or for analysis. ...
... As for the consideration of influences, the EvAAL Framework only requires the building, the path, and the entity to be localized to represent the considered application [22], while the ISO/IEC 18305 [15] additionally suggests to include particularly challenging experiments for the system under test. The T&E 4iLoc Framework [16] proposes a procedure to systematically define applicationdriven influencing factors and transpose them into an experiment in a semi-controlled test environment such as a test hall. Finally, the EVARILOS Benchmarking Handbook [23] proposes the systematic analysis of influences from changes in the environment, mobility, amount of radio-frequency nodes, or radio interference to a reference scenario individually. ...
... In step A of Figure 2, performance metrics are collected from experiments under several different scenarios. To ensure repeatability of results for the complex experiment scenario, the T&E 4iLoc Framework [16] is utilized as methodology. ...
Absolute position accuracy is the key performance criterion of an Indoor Localization System (ILS). Since ILS are heterogeneous and complex cyber-physical systems, the localization accuracy depends on various influences from the environment, system configuration, and the application processes. To determine the position accuracy of a system in a reproducible, comparable, and realistic manner, these factors must be taken into account. We propose a strategy for analyzing the influences on the position accuracy of ILS using decision trees in combination with application-related or technology-related categorization. The proposed strategy is validated using empirical data from 120 experiments. The accuracy of an Ultra-Wideband and a LiDAR-based ILS was determined under different application-driven influencing factors, considering the application of autonomous mobile robots in warehouses. Finally, the opportunities and limitations of analyzing decision trees to compare system performance, find a suitable system, optimize the environment or system configuration, and understand the relevance of different influencing factors are presented.
Introduction: Despite the plethora of sensor-based assistive technology solutions, there is still no widespread acceptance and adoption by people who are blind or have low vision (i.e., visually impaired). Many reasons prevent reducing abandonment levels with a prominent one being a lack of focus on the dimension of training, which, from our standpoint, is integral to the acceptance of assistive technologies. To prove the importance of training, we extend and validate a new version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model incorporating training as a factor. Methods: Closed- and open-ended questionnaires were given online and offline to 231 participants with visual impairments after conducting training sessions with an application for outdoor navigation by people with visual impairments developed by our research team. To assess the UTAUT extension exploratory factor analysis, confirmatory factor analysis, and structural equation model were employed to explore the relationships between the factors. A usability and user experience qualitative analysis supplemented the previous. Results: We uncovered that no factor besides performance expectancy (standardized regression weight = 0.264, p < .001) and training (standardized regression weight = 0.538, p < .001) significantly predict behavioral intention. Furthermore, the analysis demonstrated a significant interaction ( p < .007) strengthening the positive relationship between training and behavioral intention (standardized regression weight = 0.142). The qualitative analysis showed an overall positive evaluation highlighting the application's usefulness and dependability. Discussion: An application's adoption increases if individuals who are visually impaired are properly trained and acquainted with the features in real-life scenarios and recognize the application's utility for their daily lives. Implications for Practitioners: Training plays an important role in technology acceptance. It can be leveraged to make solutions more appealing to people who are visually impaired.
Several assistive technology solutions, targeting the group of Blind and Visually Impaired (BVI), have been proposed in the literature utilizing multi-sensor data fusion techniques. Furthermore, several commercial systems are currently being used in real-life scenarios by BVI individuals. However, given the rate by which new publications are made, the available review studies become quickly outdated. Moreover, there is no comparative study regarding the multi-sensor data fusion techniques between those found in the research literature and those being used in the commercial applications that many BVI individuals trust to complete their everyday activities. The objective of this study is to classify the available multi-sensor data fusion solutions found in the research literature and the commercial applications, conduct a comparative study between the most popular commercial applications (Blindsquare, Lazarillo, Ariadne GPS, Nav by ViaOpta, Seeing Assistant Move) regarding the supported features as well as compare the two most popular ones (Blindsquare and Lazarillo) with the BlindRouteVision application, developed by the authors, from the standpoint of Usability and User Experience (UX) through field testing. The literature review of sensor-fusion solutions highlights the trends of utilizing computer vision and deep learning techniques, the comparison of the commercial applications reveals their features, strengths, and weaknesses while Usability and UX demonstrate that BVI individuals are willing to sacrifice a wealth of features for more reliable navigation.
